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1. Estimation of forest leaf area index using satellite multispectral and synthetic aperture radar data in Iran

Author

Vafaei S, Fathizadeh O, Puletti N, Fadaei H, Baqer Rasooli S, and Vaglio Laurin G

Subjects
Leaf Area Index, Sentinel 2, ALOS 2, Forest Monitoring, Forestry, SD1-669.5
Abstract

Different satellite datasets, including multispectral Sentinel 2 and synthetic aperture radar Sentinel 1 and ALOS2, were tested to estimate the Leaf Area Index (LAI) in the Zagros forests, Ilam province, in Iran. Field data were collected in 61 sample plots by hemispherical photographs, to train and validate the LAI estimation models. Different satellite data combinations were used as input in regression models built with the following algorithms: Multiple Linear Regression, Random Forests, and Partial Least Square Regression. The results indicate that Leaf Area Index can be best estimated using integrated ALOS2 and Sentinel 2 data; these inputs generated the model with higher accuracy (R2 = 0.84). The combination of a single band and a vegetation index from Sentinel 2 also led to successful results (R2 = 0.81). Lower accuracy was obtained when using only ALOS 2 (R2 = 0.72), but this dataset is helpful where cloud coverage affects optical data. Sentinel 1 data was not useful for LAI prediction. The optimal model was based on the traditional Multiple Linear Regression algorithm, using a preliminary input selection step to exclude multicollinearity effects. To avoid this step, the use of Partial Least Square Regression may be an alternative, as this algorithm was able to produce estimates similar to those obtained with the best model.

Published
2021
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2. COSMO-SkyMed potential to detect and monitor Mediterranean maquis fires and regrowth: a pilot study in Capo Figari, Sardinia, Italy

Author

Vaglio Laurin G, Avezzano R, Bacciu V, Frate FD, Papale D, and Virelli M

Subjects
Cosmo-SkyMed, Maquis, Fire, Mediterranean Vegetation, Forestry, SD1-669.5
Abstract

Mediterranean maquis is a complex and widespread ecosystem in the region, intrinsically prone to fire. Many species have developed specific adaptation traits to cope with fire, ensuring resistance and resilience. Due to the recent changes in socio-economy and land uses, fires are more and more frequent in the urban-rural fringe and in the coastlines, both now densely populated. The detection of fires and the monitoring of vegetation regrowth is thus of primary interest for local management and for understanding the ecosystem dynamics and processes, also in the light of the recurrent droughts induced by climate change. Among the main objectives of the COSMO-SkyMed radar constellation mission there is the monitoring of environmental hazards; the very high revisiting time of this mission is optimal for post-hazard response activities. However, very few studies exploited such data for fire and vegetation monitoring. In this research, Cosmo-SkyMed is used in a Mediterranean protected area covered by maquis to detect the burnt area extension and to conduct a mid-term assessment of vegetation regrowth. The positive results obtained in this research highlight the importance of the very high-resolution continuous acquisitions and the multi-polarization information provided by COSMO-SkyMed for monitoring fire impacts on vegetation.

Published
2018
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3. Tree species diversity of three Ghanaian reserves

Author

Cazzolla Gatti R, Vaglio Laurin G, and Valentini R

Subjects
Ghana, Protected Areas, Forests, Database, Forestry, SD1-669.5
Abstract

Among tropical areas, Africa is considered to be poor in terms of biodiversity as compared with Amazon or South-East Asia, especially with respect to forest diversity. Despite this lower diversity, some African tropical zones, such as Ghana, harbour a plethora of species, particularly of trees. Unfortunately, as a result of anthropogenic impacts, biological diversity in West Africa dramatically decreased in the last decades, with very limited reference to evaluate the amount of the loss. Due to these growing pressure, a collection of relevant biodiversity information in this region seems to be urgent. We surveyed 127 temporary plots randomly distributed within 3 protected areas in Ghana and we collected data on tree (dbh>10 cm) species richness and their abundances. We also performed α, and β diversity analyses, and estimated the effective number of species, adopting various indices and approaches to provide further information on each assemblage. The main goals of this research were: (i) to provide a wide tree species database (abundance-based data), together with some biodiversity analyses; (ii) to estimate the sampling effort needed for next biodiversity surveys in the same and similar regions; and (iii) to calculate some indices useful to monitor the future of these protected areas both in terms of conservation and biodiversity research.

Published
2017
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4. Does degradation from selective logging and illegal activities differently impact forest resources? A case study in Ghana

Author

Vaglio Laurin G, Hawthorne William D, Chiti T, Di Paola A, Cazzolla Gatti R, Marconi S, Noce S, Grieco E, Pirotti F, and Valentini R

Subjects
Tropical Forest, Remote Sensing, Degradation, Logging, Guild, Africa, Forestry, SD1-669.5
Abstract

Degradation, a reduction of the ecosystem’s capacity to supply goods and services, is widespread in tropical forests and mainly caused by human disturbance. To maintain the full range of forest ecosystem services and support the development of effective conservation policies, we must understand the overall impact of degradation on different forest resources. This research investigates the response to disturbance of forest structure using several indicators: soil carbon content, arboreal richness and biodiversity, functional composition (guild and wood density), and productivity. We drew upon large field and remote sensing datasets from different forest types in Ghana, characterized by varied protection status, to investigate impacts of selective logging, and of illegal land use and resources extraction, which are the main disturbance causes in West Africa. Results indicate that functional composition and the overall number of species are less affected by degradation, while forest structure, soil carbon content and species abundance are seriously impacted, with resources distribution reflecting the protection level of the areas. Remote sensing analysis showed an increase in productivity in the last three decades, with higher resiliency to change in drier forest types, and stronger productivity correlation with solar radiation in the short dry season. The study region is affected by growing anthropogenic pressure on natural resources and by an increased climate variability: possible interactions of disturbance with climate are also discussed, together with the urgency to reduce degradation in order to preserve the full range of ecosystem functions.

Published
2016
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5. Co-limitation towards lower latitudes shapes global forest diversity gradients

Author

Liang, J., Gamarra, J.G.P., Picard, N., Zhou, M., Pijanowski, B., Jacobs, D.F., Reich, P.B., Crowther, T.W., Nabuurs, G.-J., de-Miguel, S., Fang, J., Woodall, C.W., Svenning, J.-C., Jucker, T., Bastin, J.-F., Wiser, S.K., Slik, F., Hérault, B., Alberti, G., Keppel, G., Hengeveld, G.M., Ibisch, P.L., Silva, C.A., ter Steege, H., Peri, P.L., Coomes, D.A., Searle, E.B., von Gadow, K., Jaroszewicz, B., Abbasi, A.O., Abegg, M., Yao, Y.C. A., Aguirre-Gutiérrez, J., Zambrano, A.M.A., Altman, J., Alvarez-Dávila, E., Álvarez-González, J.G., Alves, L.F., Amani, B.H.K., Amani, C.A., Ammer, C., Ilondea, B.A., Antón-Fernández, C., Avitabile, V., Aymard, G.A., Azihou, A.F., Baard, J.A., Baker, T.R., Balazy, R., Bastian, M.L., Batumike, R., Bauters, M., Beeckman, H., Benu, N.M.H., Bitariho, R., Boeckx, P., Bogaert, J., Bongers, F., Bouriaud, O., Brancalion, P.H.S., Brandl, S., Brearley, F. Q., Briseno-Reyes, J., Broadbent, E.N., Bruelheide, H., Bulte, E., Catlin, A.C., Cazzolla Gatti, R., César, R.G., Chen, H.Y. H., Chisholm, C., Cienciala, E., Colletta, G.D., Corral-Rivas, J.J., Cuchietti, A., Cuni-Sanchez, A., Dar, J.A., Dayanandan, S., de Haulleville, T., Decuyper, M., Delabye, S., Derroire, G., DeVries, B., Diisi, J., Do, T.V., Dolezal, J., Dourdain, A., Durrheim, G.P., Obiang, N.L.E., Ewango, C.E.N., Eyre, T.J., Fayle, T.M., Feunang, L.F.N., Finér, L., Fischer, M., Fridman, J., Frizzera, Lorenzo., de Gasper, A.L., Gianelle, D., Glick, H.B., Gonzalez-Elizondo, M.S., Gorenstein, Lev., Habonayo, R., Hardy, O.J., Harris, D.J., Hector, A., Hemp, A., Herold, M., Hillers, A., Hubau, W., Ibanez, T., Imai, N., Imani, G., Jagodzinski, A.M., Janecek, S., Johannsen, V.K., Joly, C.A., Jumbam, B., Kabelong, B. L. P. R., Kahsay, G.A., Karminov, V., Kartawinata, K., Kassi, J.ustin N., Kearsley, E., Kennard, D.K., Kepfer-Rojas, S., Khan, M. L., Kigomo, J.N., Kim, H.S., Klauberg, C., Klomberg, Y., Korjus, H., Kothandaraman, S., Kraxner, F., Kumar, A., Kuswandi, R., Lang, M., Lawes, M.J., Leite, R.V., Lentner, G., Lewis, S.L., Libalah, M.B., Lisingo, Janvier, López-Serrano, P.M., Lu, H., Lukina, N.V., Lykke, A.M., Maicher, V., Maitner, B.S., Marcon, E., Marshall, A.R., Martin, E. H., Martynenko, O., Mbayu, F.M., Mbuvi, M. T. E., Meave, J. A., Merow, C., Miscicki, S., Moreno, V. S., Morera, A., Mukul, S.A., Müller, J.C., Murdjoko, A., Nava-Miranda, M.G., Ndive, L.E., Neldner, V.J., Nevenic, R.V., Nforbelie, L.N., Ngoh, M.L., N’Guessan, A.E., Ngugi, M.R., Ngute, A. S. K., Njila, E. N. N., Nyako, M.C., Ochuodho, T.O., Oleksyn, J., Paquette, A., Parfenova, E.I., Park, M., Parren, M., Parthasarathy, N., Pfautsch, S., Phillips, O. L., Piedade, M.T. F., Piotto, D., Pollastrini, M., Poorter, L., Poulsen, J. R., Poulsen, A.D., Pretzsch, H., Rodeghiero, M., Rolim, S.G., Rovero, F., Rutishauser, E., Sagheb-Talebi, K., Saikia, P., Sainge, M.N., Salas-Eljatib, C., Salis, A., Schall, P., Shchepashchenko, D., Scherer-Lorenzen, M., Schmid, B., Schöngart, J., Šebeň, V., Sellan, G., Selvi, F., Serra-Diaz, J.M., Sheil, D., Shvidenko, A., Sist, P., Souza, A.F., Stereńczak, K.J., Sullivan, M. J. P., Sundarapandian, S., Svoboda, M., Swaine, M.D., Targhetta, N., Tchebakova, N., Trethowan, L.A., Tropek, R., Mukendi, J.T., Umunay, P.M., Usoltsev, V.A., Vaglio Laurin, G., Valentini, R., Valladares, F., van der Plas, F., Vega-Nieva, D.J., Verbeeck, H., Viana, H., Vibrans, A.C., Vieira, S.A., Vleminckx, J., Waite, C.E., Wang, H.-F., Wasingya, E.K., Wekesa, C., Westerlund, B., Wittmann, F., Wortel, V., Zawiła-Niedźwiecki, T., Zhang, C., Zhao, X., Zhu, J., Zhu, X., Zhu, Z.-X., Zo-Bi, I.C., Hui, C., Liang, J., Gamarra, J.G.P., Picard, N., Zhou, M., Pijanowski, B., Jacobs, D.F., Reich, P.B., Crowther, T.W., Nabuurs, G.-J., de-Miguel, S., Fang, J., Woodall, C.W., Svenning, J.-C., Jucker, T., Bastin, J.-F., Wiser, S.K., Slik, F., Hérault, B., Alberti, G., Keppel, G., Hengeveld, G.M., Ibisch, P.L., Silva, C.A., ter Steege, H., Peri, P.L., Coomes, D.A., Searle, E.B., von Gadow, K., Jaroszewicz, B., Abbasi, A.O., Abegg, M., Yao, Y.C. A., Aguirre-Gutiérrez, J., Zambrano, A.M.A., Altman, J., Alvarez-Dávila, E., Álvarez-González, J.G., Alves, L.F., Amani, B.H.K., Amani, C.A., Ammer, C., Ilondea, B.A., Antón-Fernández, C., Avitabile, V., Aymard, G.A., Azihou, A.F., Baard, J.A., Baker, T.R., Balazy, R., Bastian, M.L., Batumike, R., Bauters, M., Beeckman, H., Benu, N.M.H., Bitariho, R., Boeckx, P., Bogaert, J., Bongers, F., Bouriaud, O., Brancalion, P.H.S., Brandl, S., Brearley, F. Q., Briseno-Reyes, J., Broadbent, E.N., Bruelheide, H., Bulte, E., Catlin, A.C., Cazzolla Gatti, R., César, R.G., Chen, H.Y. H., Chisholm, C., Cienciala, E., Colletta, G.D., Corral-Rivas, J.J., Cuchietti, A., Cuni-Sanchez, A., Dar, J.A., Dayanandan, S., de Haulleville, T., Decuyper, M., Delabye, S., Derroire, G., DeVries, B., Diisi, J., Do, T.V., Dolezal, J., Dourdain, A., Durrheim, G.P., Obiang, N.L.E., Ewango, C.E.N., Eyre, T.J., Fayle, T.M., Feunang, L.F.N., Finér, L., Fischer, M., Fridman, J., Frizzera, Lorenzo., de Gasper, A.L., Gianelle, D., Glick, H.B., Gonzalez-Elizondo, M.S., Gorenstein, Lev., Habonayo, R., Hardy, O.J., Harris, D.J., Hector, A., Hemp, A., Herold, M., Hillers, A., Hubau, W., Ibanez, T., Imai, N., Imani, G., Jagodzinski, A.M., Janecek, S., Johannsen, V.K., Joly, C.A., Jumbam, B., Kabelong, B. L. P. R., Kahsay, G.A., Karminov, V., Kartawinata, K., Kassi, J.ustin N., Kearsley, E., Kennard, D.K., Kepfer-Rojas, S., Khan, M. L., Kigomo, J.N., Kim, H.S., Klauberg, C., Klomberg, Y., Korjus, H., Kothandaraman, S., Kraxner, F., Kumar, A., Kuswandi, R., Lang, M., Lawes, M.J., Leite, R.V., Lentner, G., Lewis, S.L., Libalah, M.B., Lisingo, Janvier, López-Serrano, P.M., Lu, H., Lukina, N.V., Lykke, A.M., Maicher, V., Maitner, B.S., Marcon, E., Marshall, A.R., Martin, E. H., Martynenko, O., Mbayu, F.M., Mbuvi, M. T. E., Meave, J. A., Merow, C., Miscicki, S., Moreno, V. S., Morera, A., Mukul, S.A., Müller, J.C., Murdjoko, A., Nava-Miranda, M.G., Ndive, L.E., Neldner, V.J., Nevenic, R.V., Nforbelie, L.N., Ngoh, M.L., N’Guessan, A.E., Ngugi, M.R., Ngute, A. S. K., Njila, E. N. N., Nyako, M.C., Ochuodho, T.O., Oleksyn, J., Paquette, A., Parfenova, E.I., Park, M., Parren, M., Parthasarathy, N., Pfautsch, S., Phillips, O. L., Piedade, M.T. F., Piotto, D., Pollastrini, M., Poorter, L., Poulsen, J. R., Poulsen, A.D., Pretzsch, H., Rodeghiero, M., Rolim, S.G., Rovero, F., Rutishauser, E., Sagheb-Talebi, K., Saikia, P., Sainge, M.N., Salas-Eljatib, C., Salis, A., Schall, P., Shchepashchenko, D., Scherer-Lorenzen, M., Schmid, B., Schöngart, J., Šebeň, V., Sellan, G., Selvi, F., Serra-Diaz, J.M., Sheil, D., Shvidenko, A., Sist, P., Souza, A.F., Stereńczak, K.J., Sullivan, M. J. P., Sundarapandian, S., Svoboda, M., Swaine, M.D., Targhetta, N., Tchebakova, N., Trethowan, L.A., Tropek, R., Mukendi, J.T., Umunay, P.M., Usoltsev, V.A., Vaglio Laurin, G., Valentini, R., Valladares, F., van der Plas, F., Vega-Nieva, D.J., Verbeeck, H., Viana, H., Vibrans, A.C., Vieira, S.A., Vleminckx, J., Waite, C.E., Wang, H.-F., Wasingya, E.K., Wekesa, C., Westerlund, B., Wittmann, F., Wortel, V., Zawiła-Niedźwiecki, T., Zhang, C., Zhao, X., Zhu, J., Zhu, X., Zhu, Z.-X., Zo-Bi, I.C., and Hui, C.

Published
2022
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6. The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations

Author

Santoro, M., Cartus, O., Carvalhais, N., Rozendaal, D.M.A., Avitabile, V., Araza, A., de Bruin, S., Herold, M., Quegan, S., Rodríguez-Veiga, P., Balzter, H., Carreiras, J., Shchepashchenko, D., Korets, M., Shimada, M., Itoh, T., Moreno Martínez, Á., Cavlovic, J., Cazzolla Gatti, R., da Conceição Bispo, P., Dewnath, N., Labrière, N., Liang, J., Lindsell, J., Mitchard, E.T.A., Morel, A., Pacheco Pascagaza, A.M., Ryan, C.M., Slik, F., Vaglio Laurin, G., Verbeeck, H., Wijaya, A., Willcock, S., Santoro, M., Cartus, O., Carvalhais, N., Rozendaal, D.M.A., Avitabile, V., Araza, A., de Bruin, S., Herold, M., Quegan, S., Rodríguez-Veiga, P., Balzter, H., Carreiras, J., Shchepashchenko, D., Korets, M., Shimada, M., Itoh, T., Moreno Martínez, Á., Cavlovic, J., Cazzolla Gatti, R., da Conceição Bispo, P., Dewnath, N., Labrière, N., Liang, J., Lindsell, J., Mitchard, E.T.A., Morel, A., Pacheco Pascagaza, A.M., Ryan, C.M., Slik, F., Vaglio Laurin, G., Verbeeck, H., Wijaya, A., and Willcock, S.

Abstract

The terrestrial forest carbon pool is poorly quantified, in particular in regions with low forest inventory capacity. By combining multiple satellite observations of synthetic aperture radar (SAR) backscatter around the year 2010, we generated a global, spatially explicit dataset of above-ground live biomass (AGB; dry mass) stored in forests with a spatial resolution of 1 ha. Using an extensive database of 110 897 AGB measurements from field inventory plots, we show that the spatial patterns and magnitude of AGB are well captured in our map with the exception of regional uncertainties in high-carbon-stock forests with AGB >250 Mg ha−1, where the retrieval was effectively based on a single radar observation. With a total global AGB of 522 Pg, our estimate of the terrestrial biomass pool in forests is lower than most estimates published in the literature (426–571 Pg). Nonetheless, our dataset increases knowledge on the spatial distribution of AGB compared to the Global Forest Resources Assessment (FRA) by the Food and Agriculture Organization (FAO) and highlights the impact of a country's national inventory capacity on the accuracy of the biomass statistics reported to the FRA. We also reassessed previous remote sensing AGB maps and identified major biases compared to inventory data, up to 120 % of the inventory value in dry tropical forests, in the subtropics and temperate zone. Because of the high level of detail and the overall reliability of the AGB spatial patterns, our global dataset of AGB is likely to have significant impacts on climate, carbon, and socio-economic modelling schemes and provides a crucial baseline in future carbon stock change estimates. The dataset is available at https://doi.org/10.1594/PANGAEA.894711 (Santoro, 2018).

Published
2021

8. Aboveground forest biomass varies across continents, ecological zones and successional stages: refined IPCC default values for tropical and subtropical forests

Author

Danaë M A Rozendaal, Daniela Requena Suarez, Veronique De Sy, Valerio Avitabile, Sarah Carter, C Y Adou Yao, Esteban Alvarez-Davila, Kristina Anderson-Teixeira, Alejandro Araujo-Murakami, Luzmila Arroyo, Benjamin Barca, Timothy R Baker, Luca Birigazzi, Frans Bongers, Anne Branthomme, Roel J W Brienen, João M B Carreiras, Roberto Cazzolla Gatti, Susan C Cook-Patton, Mathieu Decuyper, Ben DeVries, Andres B Espejo, Ted R Feldpausch, Julian Fox, Javier G P Gamarra, Bronson W Griscom, Nancy Harris, Bruno Hérault, Eurídice N Honorio Coronado, Inge Jonckheere, Eric Konan, Sara M Leavitt, Simon L Lewis, Jeremy A Lindsell, Justin Kassi N’Dja, Anny Estelle N’Guessan, Beatriz Marimon, Edward T A Mitchard, Abel Monteagudo, Alexandra Morel, Anssi Pekkarinen, Oliver L Phillips, Lourens Poorter, Lan Qie, Ervan Rutishauser, Casey M Ryan, Maurizio Santoro, Dos Santos Silayo, Plinio Sist, J W Ferry Slik, Bonaventure Sonké, Martin J P Sullivan, Gaia Vaglio Laurin, Emilio Vilanova, Maria M H Wang, Eliakimu Zahabu, Martin Herold, Rozendaal D.M.A., Requena Suarez D., De Sy V., Avitabile V., Carter S., Adou Yao C.Y., Alvarez-Davila E., Anderson-Teixeira K., Araujo-Murakami A., Arroyo L., Barca B., Baker T.R., Birigazzi L., Bongers F., Branthomme A., Brienen R.J.W., Carreiras J.M.B., Cazzolla Gatti R., Cook-Patton S.C., Decuyper M., Devries B., Espejo A.B., Feldpausch T.R., Fox J., G P Gamarra J., Griscom B.W., Harris N., Herault B., Honorio Coronado E.N., Jonckheere I., Konan E., Leavitt S.M., Lewis S.L., Lindsell J.A., N'Dja J.K., N'Guessan A.E., Marimon B., Mitchard E.T.A., Monteagudo A., Morel A., Pekkarinen A., Phillips O.L., Poorter L., Qie L., Rutishauser E., Ryan C.M., Santoro M., Silayo D.S., Sist P., Slik J.W.F., Sonke B., Sullivan M.J.P., Vaglio Laurin G., Vilanova E., Wang M.M.H., Zahabu E., Herold M., and University of St Andrews. School of Geography & Sustainable Development

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Suivi et d’évaluation, forest plot, forêt tropicale, E-DAS, Tropical and subtropical forests, 7. Clean energy, 01 natural sciences, biomasse aérienne des arbres, Laboratory of Geo-information Science and Remote Sensing, Environmental Science(all), надземная биомасса, SDG 13 - Climate Action, старовозрастные леса, General Environmental Science, GE, Enquête, IPCC, tropical and subtropical forests, Aboveground biomass, PE&RC, Forest plots, secondary and old-growth forest, Plant Production Systems, aboveground bioma, Collecte de données, P01 - Conservation de la nature et ressources foncières, Crop and Weed Ecology, aboveground biomass, GE Environmental Sciences, Monitoring, тропические леса, Secondary and old-growth forests, 010603 evolutionary biology, Objectif 13 Mesures relatives à la lutte contre les changements climatique, лесные участки, forest plots, SDG 3 - Good Health and Well-being, вторичные леса, forêt primaire, Bosecologie en Bosbeheer, Laboratorium voor Geo-informatiekunde en Remote Sensing, SDG 7 - Affordable and Clean Energy, 0105 earth and related environmental sciences, MCC, Renewable Energy, Sustainability and the Environment, Public Health, Environmental and Occupational Health, субтропические леса, 15. Life on land, Forest Ecology and Forest Management, K10 - Production forestière, secondary and old-growth forests, monitoring, 13. Climate action, Plantaardige Productiesystemen, forêt secondaire
Abstract

Funding: We acknowledge funding from the following organizations: Norwegian Agency for Development Cooperation (Norad); Norwegian International Climate and Forest Initiative (NICFI); International Climate Initiative (IKI) of the German; Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMUB); CGIAR Research Program on Forests, Trees and Agroforestry (CRP‐FTA) with financial support from the CGIAR Fund Donors; EU Horizon 2020 project VERIFY (776810); European Space Agency GlobBiomass project (ESRIN Contract No. 4000113100/14/I-NB); European Research Council (ERC) Advanced Grants T-FORCES (291585) and PANTROP (834775); JAXA (RA-6, EO-RA2); UK Natural Environment Research Council (NERC; including NE/F005806/, NE/D005590/1, NE/T01279X/1, NE/P008755/1 and NE/N012542/1); agreement PR140015 between NERC and the National Centre for Earth Observation; Gordon and Betty Moore Foundation; CNPq (National Council of Science and Technology, Brazil), Grants #401279/2014‐4 (PVE) and #441244/2016‐5 (PELD); Doris Duke Charitable Foundation; the Children's Investment 309 Fund Foundation; COmON Foundation and Good Energies Foundation. For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relatively crude estimates of average values per continent and ecological zone. The 2006 default values were based on limited plot data available at the time, methods for their derivation were not fully clear, and no distinction between successional stages was made. As part of the 2019 Refinement to the 2006 IPCC Guidelines for GHG Inventories, we updated the default AGB values for tropical and subtropical forests based on AGB data from >25 000 plots in natural forests and a global AGB map where no plot data were available. We calculated refined AGB default values per continent, ecological zone, and successional stage, and provided a measure of uncertainty. AGB in tropical and subtropical forests varies by an order of magnitude across continents, ecological zones, and successional stage. Our refined default values generally reflect the climatic gradients in the tropics, with more AGB in wetter areas. AGB is generally higher in old-growth than in secondary forests, and higher in older secondary (regrowth >20 years old and degraded/logged forests) than in young secondary forests (20 years old). While refined default values for tropical old-growth forest are largely similar to the previous 2006 default values, the new default values are 4.0-7.7-fold lower for young secondary forests. Thus, the refined values will strongly alter estimated carbon stocks and fluxes, and emphasize the critical importance of old-growth forest conservation. We provide a reproducible approach to facilitate future refinements and encourage targeted efforts to establish permanent plots in areas with data gaps. Publisher PDF

Published
2022

9. Co-limitation towards lower latitudes shapes global forest diversity gradients

Author

Jingjing Liang, Javier G. P. Gamarra, Nicolas Picard, Mo Zhou, Bryan Pijanowski, Douglass F. Jacobs, Peter B. Reich, Thomas W. Crowther, Gert-Jan Nabuurs, Sergio de-Miguel, Jingyun Fang, Christopher W. Woodall, Jens-Christian Svenning, Tommaso Jucker, Jean-Francois Bastin, Susan K. Wiser, Ferry Slik, Bruno Hérault, Giorgio Alberti, Gunnar Keppel, Geerten M. Hengeveld, Pierre L. Ibisch, Carlos A. Silva, Hans ter Steege, Pablo L. Peri, David A. Coomes, Eric B. Searle, Klaus von Gadow, Bogdan Jaroszewicz, Akane O. Abbasi, Meinrad Abegg, Yves C. Adou Yao, Jesús Aguirre-Gutiérrez, Angelica M. Almeyda Zambrano, Jan Altman, Esteban Alvarez-Dávila, Juan Gabriel Álvarez-González, Luciana F. Alves, Bienvenu H. K. Amani, Christian A. Amani, Christian Ammer, Bhely Angoboy Ilondea, Clara Antón-Fernández, Valerio Avitabile, Gerardo A. Aymard, Akomian F. Azihou, Johan A. Baard, Timothy R. Baker, Radomir Balazy, Meredith L. Bastian, Rodrigue Batumike, Marijn Bauters, Hans Beeckman, Nithanel Mikael Hendrik Benu, Robert Bitariho, Pascal Boeckx, Jan Bogaert, Frans Bongers, Olivier Bouriaud, Pedro H. S. Brancalion, Susanne Brandl, Francis Q. Brearley, Jaime Briseno-Reyes, Eben N. Broadbent, Helge Bruelheide, Erwin Bulte, Ann Christine Catlin, Roberto Cazzolla Gatti, Ricardo G. César, Han Y. H. Chen, Chelsea Chisholm, Emil Cienciala, Gabriel D. Colletta, José Javier Corral-Rivas, Anibal Cuchietti, Aida Cuni-Sanchez, Javid A. Dar, Selvadurai Dayanandan, Thales de Haulleville, Mathieu Decuyper, Sylvain Delabye, Géraldine Derroire, Ben DeVries, John Diisi, Tran Van Do, Jiri Dolezal, Aurélie Dourdain, Graham P. Durrheim, Nestor Laurier Engone Obiang, Corneille E. N. Ewango, Teresa J. Eyre, Tom M. Fayle, Lethicia Flavine N. Feunang, Leena Finér, Markus Fischer, Jonas Fridman, Lorenzo Frizzera, André L. de Gasper, Damiano Gianelle, Henry B. Glick, Maria Socorro Gonzalez-Elizondo, Lev Gorenstein, Richard Habonayo, Olivier J. Hardy, David J. Harris, Andrew Hector, Andreas Hemp, Martin Herold, Annika Hillers, Wannes Hubau, Thomas Ibanez, Nobuo Imai, Gerard Imani, Andrzej M. Jagodzinski, Stepan Janecek, Vivian Kvist Johannsen, Carlos A. Joly, Blaise Jumbam, Banoho L. P. R. Kabelong, Goytom Abraha Kahsay, Viktor Karminov, Kuswata Kartawinata, Justin N. Kassi, Elizabeth Kearsley, Deborah K. Kennard, Sebastian Kepfer-Rojas, Mohammed Latif Khan, John N. Kigomo, Hyun Seok Kim, Carine Klauberg, Yannick Klomberg, Henn Korjus, Subashree Kothandaraman, Florian Kraxner, Amit Kumar, Relawan Kuswandi, Mait Lang, Michael J. Lawes, Rodrigo V. Leite, Geoffrey Lentner, Simon L. Lewis, Moses B. Libalah, Janvier Lisingo, Pablito Marcelo López-Serrano, Huicui Lu, Natalia V. Lukina, Anne Mette Lykke, Vincent Maicher, Brian S. Maitner, Eric Marcon, Andrew R. Marshall, Emanuel H. Martin, Olga Martynenko, Faustin M. Mbayu, Musingo T. E. Mbuvi, Jorge A. Meave, Cory Merow, Stanislaw Miscicki, Vanessa S. Moreno, Albert Morera, Sharif A. Mukul, Jörg C. Müller, Agustinus Murdjoko, Maria Guadalupe Nava-Miranda, Litonga Elias Ndive, Victor J. Neldner, Radovan V. Nevenic, Louis N. Nforbelie, Michael L. Ngoh, Anny E. N’Guessan, Michael R. Ngugi, Alain S. K. Ngute, Emile Narcisse N. Njila, Melanie C. Nyako, Thomas O. Ochuodho, Jacek Oleksyn, Alain Paquette, Elena I. Parfenova, Minjee Park, Marc Parren, Narayanaswamy Parthasarathy, Sebastian Pfautsch, Oliver L. Phillips, Maria T. F. Piedade, Daniel Piotto, Martina Pollastrini, Lourens Poorter, John R. Poulsen, Axel Dalberg Poulsen, Hans Pretzsch, Mirco Rodeghiero, Samir G. Rolim, Francesco Rovero, Ervan Rutishauser, Khosro Sagheb-Talebi, Purabi Saikia, Moses Nsanyi Sainge, Christian Salas-Eljatib, Antonello Salis, Peter Schall, Dmitry Schepaschenko, Michael Scherer-Lorenzen, Bernhard Schmid, Jochen Schöngart, Vladimír Šebeň, Giacomo Sellan, Federico Selvi, Josep M. Serra-Diaz, Douglas Sheil, Anatoly Z. Shvidenko, Plinio Sist, Alexandre F. Souza, Krzysztof J. Stereńczak, Martin J. P. Sullivan, Somaiah Sundarapandian, Miroslav Svoboda, Mike D. Swaine, Natalia Targhetta, Nadja Tchebakova, Liam A. Trethowan, Robert Tropek, John Tshibamba Mukendi, Peter Mbanda Umunay, Vladimir A. Usoltsev, Gaia Vaglio Laurin, Riccardo Valentini, Fernando Valladares, Fons van der Plas, Daniel José Vega-Nieva, Hans Verbeeck, Helder Viana, Alexander C. Vibrans, Simone A. Vieira, Jason Vleminckx, Catherine E. Waite, Hua-Feng Wang, Eric Katembo Wasingya, Chemuku Wekesa, Bertil Westerlund, Florian Wittmann, Verginia Wortel, Tomasz Zawiła-Niedźwiecki, Chunyu Zhang, Xiuhai Zhao, Jun Zhu, Xiao Zhu, Zhi-Xin Zhu, Irie C. Zo-Bi, Cang Hui, Liang, Jingjing, Gamarra, Javier GP, Picard, Nicolas, Zhou, Mo, Keppel, Gunnar, Hui, Cang, Liang J., Gamarra J.G.P., Picard N., Zhou M., Pijanowski B., Jacobs D.F., Reich P.B., Crowther T.W., Nabuurs G.-J., de-Miguel S., Fang J., Woodall C.W., Svenning J.-C., Jucker T., Bastin J.-F., Wiser S.K., Slik F., Herault B., Alberti G., Keppel G., Hengeveld G.M., Ibisch P.L., Silva C.A., ter Steege H., Peri P.L., Coomes D.A., Searle E.B., von Gadow K., Jaroszewicz B., Abbasi A.O., Abegg M., Yao Y.C.A., Aguirre-Gutierrez J., Zambrano A.M.A., Altman J., Alvarez-Davila E., Alvarez-Gonzalez J.G., Alves L.F., Amani B.H.K., Amani C.A., Ammer C., Ilondea B.A., Anton-Fernandez C., Avitabile V., Aymard G.A., Azihou A.F., Baard J.A., Baker T.R., Balazy R., Bastian M.L., Batumike R., Bauters M., Beeckman H., Benu N.M.H., Bitariho R., Boeckx P., Bogaert J., Bongers F., Bouriaud O., Brancalion P.H.S., Brandl S., Brearley F.Q., Briseno-Reyes J., Broadbent E.N., Bruelheide H., Bulte E., Catlin A.C., Cazzolla Gatti R., Cesar R.G., Chen H.Y.H., Chisholm C., Cienciala E., Colletta G.D., Corral-Rivas J.J., Cuchietti A., Cuni-Sanchez A., Dar J.A., Dayanandan S., de Haulleville T., Decuyper M., Delabye S., Derroire G., DeVries B., Diisi J., Do T.V., Dolezal J., Dourdain A., Durrheim G.P., Obiang N.L.E., Ewango C.E.N., Eyre T.J., Fayle T.M., Feunang L.F.N., Finer L., Fischer M., Fridman J., Frizzera L., de Gasper A.L., Gianelle D., Glick H.B., Gonzalez-Elizondo M.S., Gorenstein L., Habonayo R., Hardy O.J., Harris D.J., Hector A., Hemp A., Herold M., Hillers A., Hubau W., Ibanez T., Imai N., Imani G., Jagodzinski A.M., Janecek S., Johannsen V.K., Joly C.A., Jumbam B., Kabelong B.L.P.R., Kahsay G.A., Karminov V., Kartawinata K., Kassi J.N., Kearsley E., Kennard D.K., Kepfer-Rojas S., Khan M.L., Kigomo J.N., Kim H.S., Klauberg C., Klomberg Y., Korjus H., Kothandaraman S., Kraxner F., Kumar A., Kuswandi R., Lang M., Lawes M.J., Leite R.V., Lentner G., Lewis S.L., Libalah M.B., Lisingo J., Lopez-Serrano P.M., Lu H., Lukina N.V., Lykke A.M., Maicher V., Maitner B.S., Marcon E., Marshall A.R., Martin E.H., Martynenko O., Mbayu F.M., Mbuvi M.T.E., Meave J.A., Merow C., Miscicki S., Moreno V.S., Morera A., Mukul S.A., Muller J.C., Murdjoko A., Nava-Miranda M.G., Ndive L.E., Neldner V.J., Nevenic R.V., Nforbelie L.N., Ngoh M.L., N'Guessan A.E., Ngugi M.R., Ngute A.S.K., Njila E.N.N., Nyako M.C., Ochuodho T.O., Oleksyn J., Paquette A., Parfenova E.I., Park M., Parren M., Parthasarathy N., Pfautsch S., Phillips O.L., Piedade M.T.F., Piotto D., Pollastrini M., Poorter L., Poulsen J.R., Poulsen A.D., Pretzsch H., Rodeghiero M., Rolim S.G., Rovero F., Rutishauser E., Sagheb-Talebi K., Saikia P., Sainge M.N., Salas-Eljatib C., Salis A., Schall P., Schepaschenko D., Scherer-Lorenzen M., Schmid B., Schongart J., Seben V., Sellan G., Selvi F., Serra-Diaz J.M., Sheil D., Shvidenko A.Z., Sist P., Souza A.F., Sterenczak K.J., Sullivan M.J.P., Sundarapandian S., Svoboda M., Swaine M.D., Targhetta N., Tchebakova N., Trethowan L.A., Tropek R., Mukendi J.T., Umunay P.M., Usoltsev V.A., Vaglio Laurin G., Valentini R., Valladares F., van der Plas F., Vega-Nieva D.J., Verbeeck H., Viana H., Vibrans A.C., Vieira S.A., Vleminckx J., Waite C.E., Wang H.-F., Wasingya E.K., Wekesa C., Westerlund B., Wittmann F., Wortel V., Zawila-Niedzwiecki T., Zhang C., Zhao X., Zhu J., Zhu X., Zhu Z.-X., Zo-Bi I.C., Hui C., Purdue University [West Lafayette], Food and Agriculture Organization of the United Nations [Rome, Italie] (FAO), Groupement d'Interêt Public Ecosystèmes Forestiers GIP ECOFOR (GIP ECOFOR ), Forêts et Sociétés (UPR Forêts et Sociétés), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Département Environnements et Sociétés (Cirad-ES), Ecologie des forêts de Guyane (UMR ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université de Montpellier (UM), SILVA (SILVA), AgroParisTech-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National Polytechnique Félix Houphouët-Boigny, and Stellenbosch University

Subjects
Bos- en Landschapsecologie, WASS, Plant Ecology and Nature Conservation, Forests, [SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, Co-limitation, Ontwikkelingseconomie, Forest and Nature Conservation Policy, Trees, Soil, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, Development Economics, Laboratory of Geo-information Science and Remote Sensing, Settore BIO/07 - ECOLOGIA, Life Science, Laboratorium voor Moleculaire Biologie, Bos- en Natuurbeleid, Forest and Landscape Ecology, Bosecologie en Bosbeheer, Laboratorium voor Geo-informatiekunde en Remote Sensing, BIOS Plant Development Systems, Vegetatie, Ecology, Evolution, Behavior and Systematics, biogeography, biodiversity, Vegetation, Ecology, Biodiversity, [SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics, Latitudinal gradients, PE&RC, Forest Ecology and Forest Management, Bioclimatic dominance, Biogeography, LATITUDE, Plantenecologie en Natuurbeheer, Vegetatie, Bos- en Landschapsecologie, Vegetation, Forest and Landscape Ecology, Laboratory of Molecular Biology, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Corporate Governance & Legal Services, Tree, Global LDG
Abstract

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers. The team collaboration and manuscript development are supported by the web-based team science platform: science-i.org, with the project number 202205GFB2. We thank the following initiatives, agencies, teams and individuals for data collection and other technical support: the Global Forest Biodiversity Initiative (GFBI) for establishing the data standards and collaborative framework; United States Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program; University of Alaska Fairbanks; the SODEFOR, Ivory Coast; University Félix Houphouët-Boigny (UFHB, Ivory Coast); the Queensland Herbarium and past Queensland Government Forestry and Natural Resource Management departments and staff for data collection for over seven decades; and the National Forestry Commission of Mexico (CONAFOR). We thank M. Baker (Carbon Tanzania), together with a team of field assistants (Valentine and Lawrence); all persons who made the Third Spanish Forest Inventory possible, especially the main coordinator, J. A. Villanueva (IFN3); the French National Forest Inventory (NFI campaigns (raw data 2005 and following annual surveys, were downloaded by GFBI at https://inventaire-forestier.ign.fr/spip.php?rubrique159; site accessed on 1 January 2015)); the Italian Forest Inventory (NFI campaigns raw data 2005 and following surveys were downloaded by GFBI at https://inventarioforestale.org/; site accessed on 27 April 2019); Swiss National Forest Inventory, Swiss Federal Institute for Forest, Snow and Landscape Research WSL and Federal Office for the Environment FOEN, Switzerland; the Swedish NFI, Department of Forest Resource Management, Swedish University of Agricultural Sciences SLU; the National Research Foundation (NRF) of South Africa (89967 and 109244) and the South African Research Chair Initiative; the Danish National Forestry, Department of Geosciences and Natural Resource Management, UCPH; Coordination for the Improvement of Higher Education Personnel of Brazil (CAPES, grant number 88881.064976/2014-01); R. Ávila and S. van Tuylen, Instituto Nacional de Bosques (INAB), Guatemala, for facilitating Guatemalan data; the National Focal Center for Forest condition monitoring of Serbia (NFC), Institute of Forestry, Belgrade, Serbia; the Thünen Institute of Forest Ecosystems (Germany) for providing National Forest Inventory data; the FAO and the United Nations High Commissioner for Refugees (UNHCR) for undertaking the SAFE (Safe Access to Fuel and Energy) and CBIT-Forest projects; and the Amazon Forest Inventory Network (RAINFOR), the African Tropical Rainforest Observation Network (AfriTRON) and the ForestPlots.net initiative for their contributions from Amazonian and African forests. The Natural Forest plot data collected between January 2009 and March 2014 by the LUCAS programme for the New Zealand Ministry for the Environment are provided by the New Zealand National Vegetation Survey Databank https://nvs.landcareresearch.co.nz/. We thank the International Boreal Forest Research Association (IBFRA); the Forestry Corporation of New South Wales, Australia; the National Forest Directory of the Ministry of Environment and Sustainable Development of the Argentine Republic (MAyDS) for the plot data of the Second National Forest Inventory (INBN2); the National Forestry Authority and Ministry of Water and Environment of Uganda for their National Biomass Survey (NBS) dataset; and the Sabah Biodiversity Council and the staff from Sabah Forest Research Centre. All TEAM data are provided by the Tropical Ecology Assessment and Monitoring (TEAM) Network, a collaboration between Conservation International, the Missouri Botanical Garden, the Smithsonian Institution and the Wildlife Conservation Society, and partially funded by these institutions, the Gordon and Betty Moore Foundation and other donors, with thanks to all current and previous TEAM site manager and other collaborators that helped collect data. We thank the people of the Redidoti, Pierrekondre and Cassipora village who were instrumental in assisting with the collection of data and sharing local knowledge of their forest and the dedicated members of the field crew of Kabo 2012 census. We are also thankful to FAPESC, SFB, FAO and IMA/SC for supporting the IFFSC. This research was supported in part through computational resources provided by Information Technology at Purdue, West Lafayette, Indiana.This work is supported in part by the NASA grant number 12000401 ‘Multi-sensor biodiversity framework developed from bioacoustic and space based sensor platforms’ (J. Liang, B.P.); the USDA National Institute of Food and Agriculture McIntire Stennis projects 1017711 (J. Liang) and 1016676 (M.Z.); the US National Science Foundation Biological Integration Institutes grant NSF‐DBI‐2021898 (P.B.R.); the funding by H2020 VERIFY (contract 776810) and H2020 Resonate (contract 101000574) (G.-J.N.); the TEAM project in Uganda supported by the Moore foundation and Buffett Foundation through Conservation International (CI) and Wildlife Conservation Society (WCS); the Danish Council for Independent Research | Natural Sciences (TREECHANGE, grant 6108- 00078B) and VILLUM FONDEN grant number 16549 (J.-C.S.); the Natural Environment Research Council of the UK (NERC) project NE/T011084/1 awarded to J.A.-G. and NE/S011811/1; ERC Advanced Grant 291585 (‘T-FORCES’) and a Royal Society-Wolfson Research Merit Award (O.L.P.); RAINFOR plots supported by the Gordon and Betty Moore Foundation and the UK Natural Environment Research Council, notably NERC Consortium Grants ‘AMAZONICA’ (NE/F005806/1), ‘TROBIT’ (NE/D005590/1) and ‘BIO-RED’ (NE/N012542/1); CIFOR’s Global Comparative Study on REDD+ funded by the Norwegian Agency for Development Cooperation, the Australian Department of Foreign Affairs and Trade, the European Union, the International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety and the CGIAR Research Program on Forests, Trees and Agroforestry (CRP-FTA) and donors to the CGIAR Fund; AfriTRON network plots funded by the local communities and NERC, ERC, European Union, Royal Society and Leverhume Trust; a grant from the Royal Society and the Natural Environment Research Council, UK (S.L.L.); National Science Foundation CIF21 DIBBs: EI: number 1724728 (A.C.C.); National Natural Science Foundation of China (31800374) and Shandong Provincial Natural Science Foundation (ZR2019BC083) (H.L.). UK NERC Independent Research Fellowship (grant code: NE/S01537X/1) (T.J.); a Serra-Húnter Fellowship provided by the Government of Catalonia (Spain) (S.d.-M.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.A.S.); a grant from the Franklinia Foundation (D.A.C.); Russian Science Foundation project number 19-77-300-12 (R.V.); the Takenaka Scholarship Foundation (A.O.A.); the German Research Foundation (DFG), grant number Am 149/16-4 (C.A.); the Romania National Council for Higher Education Funding, CNFIS, project number CNFIS-FDI-2022-0259 (O.B.); Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-05109 and STPGP506284) and the Canadian Foundation for Innovation (36014) (H.Y.H.C.); the project SustES—Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797) (E.C.); Consejo de Ciencia y Tecnología del estado de Durango (2019-01-155) (J.J.C.-R.); Science and Engineering Research Board (SERB), New Delhi, Government of India (file number PDF/2015/000447)— ‘Assessing the carbon sequestration potential of different forest types in Central India in response to climate change’ (J.A.D.); Investissement d’avenir grant of the ANR (CEBA: ANR-10-LABEX-0025) (G.D.); National Foundation for Science & Technology Development of Vietnam, 106-NN.06-2013.01 (T.V.D.); Queensland government, Department of Environment and Science (T.J.E.); a Czech Science Foundation Standard grant (19-14620S) (T.M.F.); European Union Seventh Framework Program (FP7/2007– 2013) under grant agreement number 265171 (L. Finer, M. Pollastrini, F. Selvi); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (J.F.); CNPq productivity grant number 311303/2020-0 (A.L.d.G.); DFG grant HE 2719/11-1,2,3; HE 2719/14-1 (A. Hemp); European Union’s Horizon Europe research project OpenEarthMonitor grant number 101059548, CGIAR Fund INIT-32-MItigation and Transformation Initiative for GHG reductions of Agrifood systems RelaTed Emissions (MITIGATE+) (M.H.); General Directorate of the State Forests, Poland (1/07; OR-2717/3/11; OR.271.3.3.2017) and the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (A.M.J.); Czech Science Foundation 18-10781 S (S.J.); Danish of Ministry of Environment, the Danish Environmental Protection Agency, Integrated Forest Monitoring Program—NFI (V.K.J.); State of São Paulo Research Foundation/FAPESP as part of the BIOTA/FAPESP Program Project Functional Gradient-PELD/BIOTA-ECOFOR 2003/12595-7 & 2012/51872-5 (C.A.J.); Danish Council for Independent Research—social sciences—grant DFF 6109– 00296 (G.A.K.); Russian Science Foundation project 21-46-07002 for the plot data collected in the Krasnoyarsk region (V.K.); BOLFOR (D.K.K.); Department of Biotechnology, New Delhi, Government of India (grant number BT/PR7928/ NDB/52/9/2006, dated 29 September 2006) (M.L.K.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (J.N.K.); Korea Forest Service (2018113A00-1820-BB01, 2013069A00-1819-AA03, and 2020185D10- 2022-AA02) and Seoul National University Big Data Institute through the Data Science Research Project 2016 (H.S.K.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.K.); CSIR, New Delhi, government of India (grant number 38(1318)12/EMR-II, dated: 3 April 2012) (S.K.); Department of Biotechnology, New Delhi, government of India (grant number BT/ PR12899/ NDB/39/506/2015 dated 20 June 2017) (A.K.); Coordination for the Improvement of Higher Education Personnel (CAPES) #88887.463733/2019-00 (R.V.L.); National Natural Science Foundation of China (31800374) (H.L.); project of CEPF RAS ‘Methodological approaches to assessing the structural organization and functioning of forest ecosystems’ (AAAA-A18-118052590019-7) funded by the Ministry of Science and Higher Education of Russia (N.V.L.); Leverhulme Trust grant to Andrew Balmford, Simon Lewis and Jon Lovett (A.R.M.); Russian Science Foundation, project 19-77-30015 for European Russia data processing (O.M.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (M.T.E.M.); the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (S.M.); the Secretariat for Universities and of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund (A. Morera); Queensland government, Department of Environment and Science (V.J.N.); Pinnacle Group Cameroon PLC (L.N.N.); Queensland government, Department of Environment and Science (M.R.N.); the Natural Sciences and Engineering Research Council of Canada (RGPIN-2018-05201) (A.P.); the Russian Foundation for Basic Research, project number 20-05-00540 (E.I.P.); European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 778322 (H.P.); Science and Engineering Research Board, New Delhi, government of India (grant number YSS/2015/000479, dated 12 January 2016) (P.S.); the Chilean Government research grants Fondecyt number 1191816 and FONDEF number ID19 10421 (C.S.-E.); the Deutsche Forschungsgemeinschaft (DFG) Priority Program 1374 Biodiversity Exploratories (P.S.); European Space Agency projects IFBN (4000114425/15/NL/FF/gp) and CCI Biomass (4000123662/18/I-NB) (D. Schepaschenko); FunDivEUROPE, European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement number 265171 (M.S.-L.); APVV 20-0168 from the Slovak Research and Development Agency (V.S.); Manchester Metropolitan University’s Environmental Science Research Centre (G.S.); the project ‘LIFE+ ForBioSensing PL Comprehensive monitoring of stand dynamics in Białowieża Forest supported with remote sensing techniques’ which is co-funded by the EU Life Plus programme (contract number LIFE13 ENV/PL/000048) and the National Fund for Environmental Protection and Water Management in Poland (contract number 485/2014/WN10/OP-NM-LF/D) (K.J.S.); Global Challenges Research Fund (QR allocation, MMU) (M.J.P.S.); Czech Science Foundation project 21-27454S (M.S.); the Russian Foundation for Basic Research, project number 20-05-00540 (N. Tchebakova); Botanical Research Fund, Coalbourn Trust, Bentham Moxon Trust, Emily Holmes scholarship (L.A.T.); the programmes of the current scientific research of the Botanical Garden of the Ural Branch of Russian Academy of Sciences (V.A.U.); FCT—Portuguese Foundation for Science and Technology—Project UIDB/04033/2020. Inventário Florestal Nacional—ICNF (H. Viana); Grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (C.W.); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (B.W.); ATTO project (grant number MCTI-FINEP 1759/10 and BMBF 01LB1001A, 01LK1602F) (F.W.); ReVaTene/ PReSeD-CI 2 is funded by the Education and Research Ministry of Côte d’Ivoire, as part of the Debt Reduction-Development Contracts (C2Ds) managed by IRD (I.C.Z.-B.); the National Research Foundation of South Africa (NRF, grant 89967) (C.H.). The Tropical Plant Exploration Group 70 1 ha plots in Continental Cameroon Mountains are supported by Rufford Small Grant Foundation, UK and 4 ha in Sierra Leone are supported by the Global Challenge Research Fund through Manchester Metropolitan University, UK; the National Geographic Explorer Grant, NGS-53344R-18 (A.C.-S.); University of KwaZulu-Natal Research Office grant (M.J.L.); Universidad Nacional Autónoma de México, Dirección General de Asuntos de Personal Académico, Grant PAPIIT IN-217620 (J.A.M.). Czech Science Foundation project 21-24186M (R.T., S. Delabye). Czech Science Foundation project 20-05840Y, the Czech Ministry of Education, Youth and Sports (LTAUSA19137) and the long-term research development project of the Czech Academy of Sciences no. RVO 67985939 (J.A.). The American Society of Primatologists, the Duke University Graduate School, the L.S.B. Leakey Foundation, the National Science Foundation (grant number 0452995) and the Wenner-Gren Foundation for Anthropological Research (grant number 7330) (M.B.). Research grants from Conselho Nacional de Desenvolvimento Científico e Tecnologico (CNPq, Brazil) (309764/2019; 311303/2020) (A.C.V., A.L.G.). The Project of Sanya Yazhou Bay Science and Technology City (grant number CKJ-JYRC-2022-83) (H.-F.W.). The Ugandan NBS was supported with funds from the Forest Carbon Partnership Facility (FCPF), the Austrian Development Agency (ADC) and FAO. FAO’s UN-REDD Program, together with the project on ‘Native Forests and Community’ Loan BIRF number 8493-AR UNDP ARG/15/004 and the National Program for the Protection of Native Forests under UNDP funded Argentina’s INBN2.

Published
2022

10. Does degradation from selective logging and illegal activities differently impact forest resources? A case study in Ghana

Author

R. Cazzolla Gatti, G. Vaglio Laurin, Tommaso Chiti, Riccardo Valentini, Elisa Grieco, Sergio Noce, Sergio Marconi, William D. Hawthorne, Francesco Pirotti, A. Di Paola, Vaglio Laurin G., Hawthorne W.D., Chiti T., Di Paola A., Cazzolla Gatti R., Marconi S., Noce S., Grieco E., Pirotti F., and Valentini R.

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Forest management, Africa, Degradation, Guild, Logging, Remote sensing, Tropical forest, Forestry, Ecology, Nature and Landscape Conservation, 010603 evolutionary biology, 01 natural sciences, Forest restoration, Remote Sensing, Forest ecology, Tropical Forest, lcsh:Forestry, Intact forest landscape, 0105 earth and related environmental sciences, 2. Zero hunger, Forest floor, geography, geography.geographical_feature_category, Agroforestry, 15. Life on land, Old-growth forest, Disturbance (ecology), 13. Climate action, Environmental science, Secondary forest, lcsh:SD1-669.5
Abstract

Degradation, a reduction of the ecosystem’s capacity to supply goods and services, is widespread in tropical forests and mainly caused by human disturbance. To maintain the full range of forest ecosystem services and support the development of effective conservation policies, we must understand the overall impact of degradation on different forest resources. This research investigates the response to disturbance of forest structure using several indicators: soil carbon content, arboreal richness and biodiversity, functional composition (guild and wood density), and productivity. We drew upon large field and remote sensing datasets from different forest types in Ghana, characterized by varied protection status, to investigate impacts of selective logging, and of illegal land use and resources extraction, which are the main disturbance causes in West Africa. Results indicate that functional composition and the overall number of species are less affected by degradation, while forest structure, soil carbon content and species abundance are seriously impacted, with resources distribution reflecting the protection level of the areas. Remote sensing analysis showed an increase in productivity in the last three decades, with higher resiliency to change in drier forest types, and stronger productivity correlation with solar radiation in the short dry season. The study region is affected by growing anthropogenic pressure on natural resources and by an increased climate variability: possible interactions of disturbance with climate are also discussed, together with the urgency to reduce degradation in order to preserve the full range of ecosystem functions.

Published
2016

11. Co-limitation towards lower latitudes shapes global forest diversity gradients.

Author

Liang J, Gamarra JGP, Picard N, Zhou M, Pijanowski B, Jacobs DF, Reich PB, Crowther TW, Nabuurs GJ, de-Miguel S, Fang J, Woodall CW, Svenning JC, Jucker T, Bastin JF, Wiser SK, Slik F, Hérault B, Alberti G, Keppel G, Hengeveld GM, Ibisch PL, Silva CA, Ter Steege H, Peri PL, Coomes DA, Searle EB, von Gadow K, Jaroszewicz B, Abbasi AO, Abegg M, Yao YCA, Aguirre-Gutiérrez J, Zambrano AMA, Altman J, Alvarez-Dávila E, Álvarez-González JG, Alves LF, Amani BHK, Amani CA, Ammer C, Ilondea BA, Antón-Fernández C, Avitabile V, Aymard GA, Azihou AF, Baard JA, Baker TR, Balazy R, Bastian ML, Batumike R, Bauters M, Beeckman H, Benu NMH, Bitariho R, Boeckx P, Bogaert J, Bongers F, Bouriaud O, Brancalion PHS, Brandl S, Brearley FQ, Briseno-Reyes J, Broadbent EN, Bruelheide H, Bulte E, Catlin AC, Cazzolla Gatti R, César RG, Chen HYH, Chisholm C, Cienciala E, Colletta GD, Corral-Rivas JJ, Cuchietti A, Cuni-Sanchez A, Dar JA, Dayanandan S, de Haulleville T, Decuyper M, Delabye S, Derroire G, DeVries B, Diisi J, Do TV, Dolezal J, Dourdain A, Durrheim GP, Obiang NLE, Ewango CEN, Eyre TJ, Fayle TM, Feunang LFN, Finér L, Fischer M, Fridman J, Frizzera L, de Gasper AL, Gianelle D, Glick HB, Gonzalez-Elizondo MS, Gorenstein L, Habonayo R, Hardy OJ, Harris DJ, Hector A, Hemp A, Herold M, Hillers A, Hubau W, Ibanez T, Imai N, Imani G, Jagodzinski AM, Janecek S, Johannsen VK, Joly CA, Jumbam B, Kabelong BLPR, Kahsay GA, Karminov V, Kartawinata K, Kassi JN, Kearsley E, Kennard DK, Kepfer-Rojas S, Khan ML, Kigomo JN, Kim HS, Klauberg C, Klomberg Y, Korjus H, Kothandaraman S, Kraxner F, Kumar A, Kuswandi R, Lang M, Lawes MJ, Leite RV, Lentner G, Lewis SL, Libalah MB, Lisingo J, López-Serrano PM, Lu H, Lukina NV, Lykke AM, Maicher V, Maitner BS, Marcon E, Marshall AR, Martin EH, Martynenko O, Mbayu FM, Mbuvi MTE, Meave JA, Merow C, Miscicki S, Moreno VS, Morera A, Mukul SA, Müller JC, Murdjoko A, Nava-Miranda MG, Ndive LE, Neldner VJ, Nevenic RV, Nforbelie LN, Ngoh ML, N'Guessan AE, Ngugi MR, Ngute ASK, Njila ENN, Nyako MC, Ochuodho TO, Oleksyn J, Paquette A, Parfenova EI, Park M, Parren M, Parthasarathy N, Pfautsch S, Phillips OL, Piedade MTF, Piotto D, Pollastrini M, Poorter L, Poulsen JR, Poulsen AD, Pretzsch H, Rodeghiero M, Rolim SG, Rovero F, Rutishauser E, Sagheb-Talebi K, Saikia P, Sainge MN, Salas-Eljatib C, Salis A, Schall P, Schepaschenko D, Scherer-Lorenzen M, Schmid B, Schöngart J, Šebeň V, Sellan G, Selvi F, Serra-Diaz JM, Sheil D, Shvidenko AZ, Sist P, Souza AF, Stereńczak KJ, Sullivan MJP, Sundarapandian S, Svoboda M, Swaine MD, Targhetta N, Tchebakova N, Trethowan LA, Tropek R, Mukendi JT, Umunay PM, Usoltsev VA, Vaglio Laurin G, Valentini R, Valladares F, van der Plas F, Vega-Nieva DJ, Verbeeck H, Viana H, Vibrans AC, Vieira SA, Vleminckx J, Waite CE, Wang HF, Wasingya EK, Wekesa C, Westerlund B, Wittmann F, Wortel V, Zawiła-Niedźwiecki T, Zhang C, Zhao X, Zhu J, Zhu X, Zhu ZX, Zo-Bi IC, and Hui C

Subjects
Soil, Trees, Biodiversity, Forests
Abstract

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Published
2022
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12. Monitoring tropical forests under a functional perspective with satellite-based vegetation optical depth.

Author

Vaglio Laurin G, Vittucci C, Tramontana G, Ferrazzoli P, Guerriero L, and Papale D

Subjects
Africa, Climate Change, South America, Trees, Ecosystem, Forests
Abstract

Monitoring ecosystem functions in forests is a priority in a climate change scenario, as climate-induced events may initially alter the functions more than slow-changing attributes, such as biomass. The ecosystem functional properties (EFPs) are quantities that characterize key ecosystem processes. They can be derived by point observations of gas and energy exchanges between the ecosystems and the atmosphere that are collected globally at FLUXNET flux tower sites and upscaled at ecosystem level. The properties here considered describe the ability of ecosystems to optimize the use of resources for carbon uptake. They represent functional forest information, are dependent on environmental drivers, linked to leaf traits and forest structure, and influenced by climate change effects. The ability of vegetation optical depth (VOD) to provide forest functional information is investigated using 2011-2014 satellite data collected by the Soil Moisture and Ocean Salinity mission and using the EFPs as reference dataset. Tropical forests in Africa and South America were analyzed, also according to ecological homogeneous units. VOD jointly with water deficit information explained 93% and 87% of the yearly variability in both flux upscaled maximum gross primary productivity and light use efficiency functional properties, in Africa and South America forests respectively. Maps of the retrieved properties evidenced changes in forest functional responses linked to anomalous climate-induced events during the study period. The findings indicate that VOD can support the flux upscaling process in the tropical range, affected by high uncertainty, and the detection of forest anomalous functional responses. Preliminary temporal analysis of VOD and EFP signals showed fine-grained variability in periodicity, in signal dephasing, and in the strength of the relationships. In selected drier forest types, these satellite data could also support the monitoring of functional dynamics., (© 2020 John Wiley & Sons Ltd.)

Published
2020
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